Laguna XS 2.1 (Reasoning) vs GLM-4.7-Flash (Reasoning)
Results updated 8 November 2026 · In Terminus-2 and Claude Code, so part of any gap can come from the harness · How we benchmark
Verdict
GLM-4.7-Flash (Reasoning) beats Laguna XS 2.1 (Reasoning) by 4 points, and is faster; Laguna XS 2.1 (Reasoning) is cheaper.
- Cost per task
- $0.054 vs $0.27
- Time per task
- 17.3 min vs 3.8 min
- Tokens per attempt
- 937k vs 1.34M
- Image input
- No vs No
Laguna XS 2.1 (Reasoning), Terminus-2 scores higher on Earth-Bench V2; GLM-4.7-Flash (Reasoning), Claude Code scores higher on GeoBenchX and GS-QA2. Laguna XS 2.1 (Reasoning), Terminus-2 is cheaper ($0.054 against $0.27 per task), but GLM-4.7-Flash (Reasoning), Claude Code is faster (3.8 min against 17.3 min).
Where they differ most
By kind of work, share of tasks passed, 0 to 100 · Higher is better
| Kind of work | Laguna XS 2.1 (Reasoning) | GLM-4.7-Flash (Reasoning) |
|---|---|---|
| GIS analysis | 35 | 49 |
| Change detection | 48 | 40 |
| Making maps | 53 | 49 |
| Remote sensing and raster analysis | 39 | 42 |
Where the tasks are set: each kind of work links to its tasks and scoresCharts for each: Laguna XS 2.1 (Reasoning), Terminus-2 · GLM-4.7-Flash (Reasoning), Claude Code.
Side by side
| Metric | Laguna XS 2.1 (Reasoning), Terminus-2 | GLM-4.7-Flash (Reasoning), Claude Code |
|---|---|---|
| Geospatial Agent Index: Text only | 37 | 41 |
| Geospatial Agent Index: Text + vision | No data | No image input |
| Earth-Bench V2 score | 44 | 38 |
| GeoBenchX score | 33 | 39 |
| GS-QA2 score | 35 | 48 |
| Vision agents score | No data | No image input |
| GeoAgentBench score (Guided workflows; not in the Agent Index) | 63 | 30 |
| GeoAnalystBench score (Guided workflows; not in the Agent Index) | 63 | 26 |
| OGD4All score (standalone; in no index) | 65 | No data |
| GeoNatureAgent score (standalone; in no index) | 36 | No data |
| MultiGlobeQA score (standalone; in no index) | 59 | No data |
| GeoAgentEval score (standalone; in no index) | 60 | No data |
| ImpactMesh score (standalone; in no index) | No data | No data |
| Remote sensing and raster analysis score | 39 | 42 |
| Change detection score | 48 | 40 |
| GIS analysis score | 35 | 49 |
| Climate and time series score | 36 | 38 |
| Making maps score | 53 | 49 |
| Cost per task | $0.054 | $0.27 |
| Time per task (at 100 output tokens/s) | 17.3 min | 3.8 min |
| Tokens per attempt | 937k | 1.34M |
| Turns per attempt | 36.7 | 37.8 |
| Input price per 1M tokens | $0.10 | $0.070 |
| Output price per 1M tokens | $0.20 | $0.40 |
| Context window | 262,144 | 131,072 |
| Image input | No | No |
| Developer | Poolside | Z.ai |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Laguna XS 2.1 (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
GLM-4.7-Flash (Reasoning), Claude Code, 41 to 37.
Which is cheaper per task, Laguna XS 2.1 (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
Laguna XS 2.1 (Reasoning), Terminus-2, $0.054 to $0.27.
Which writes fewer output tokens per task, Laguna XS 2.1 (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
GLM-4.7-Flash (Reasoning), Claude Code, 15k to 24k.
Which has the larger context window, Laguna XS 2.1 (Reasoning), Terminus-2 or GLM-4.7-Flash (Reasoning), Claude Code?
Laguna XS 2.1 (Reasoning), Terminus-2, 262,144 tokens to 131,072 tokens.